Shows how we can use remote sensing to study natural phenomena that vary seasonally but whose timing is affected by both shorter- and longer-term variations in climate or other, similar environmental conditions.

Combining genetic data with current and predicted climate scenarios, we are modeling the predicted future distributions of wildlife populations in the Arctic and identifying key environmental variables that determine important animal habitat.

Over 30 years of substantial warming, the timing of life cycle events in maize here has changed, threatening the crop yield by exposing the plant at sensitive phases in its life cycle to increased heat and drought, and lowering the weight of its grains.